Mathematical models in drug design MCQs With Answer

Mathematical models in drug design combine pharmacokinetics, pharmacodynamics, computational modeling, and statistical tools to predict drug behavior and optimize candidate molecules. For B. Pharm students, understanding compartmental models, PK/PD relationships, QSAR, docking scores, PBPK simulations, and parameter estimation is essential for rational drug discovery. These models help quantify ADME processes, forecast dose–response using Michaelis–Menten or Hill equations, guide molecular optimization with QSAR descriptors, and evaluate variability through population PK and Monte Carlo simulations. Familiarity with model validation metrics (R², AIC), sensitivity analysis, and scaling approaches enhances evidence-based formulation and dosage design. Now let’s test your knowledge with 30 MCQs on this topic.

Q1. What is a compartmental model in pharmacokinetics?

  • A mathematical framework dividing the body into interconnected compartments with rate constants
  • A method to measure drug concentration only in blood samples
  • A qualitative description of drug taste and solubility
  • A graphical tool for chemical structure representation

Correct Answer: A mathematical framework dividing the body into interconnected compartments with rate constants

Q2. Which parameter represents the volume in which a drug appears to be distributed?

  • Clearance (Cl)
  • Volume of distribution (Vd)
  • Elimination rate constant (ke)
  • Bioavailability (F)

Correct Answer: Volume of distribution (Vd)

Q3. In a one-compartment IV bolus model, the concentration–time profile follows which equation?

  • Exponential decline: C = C0 · e^(−ke·t)
  • Linear increase: C = C0 + ke·t
  • Logistic growth curve
  • Polynomial decay of second order

Correct Answer: Exponential decline: C = C0 · e^(−ke·t)

Q4. What does AUC (area under the concentration–time curve) estimate?

  • Total drug exposure over time

Correct Answer: Total drug exposure over time

Q5. Which equation describes saturable (nonlinear) elimination kinetics?

  • First-order elimination equation
  • Michaelis–Menten equation: v = (Vmax · C)/(Km + C)
  • Henderson–Hasselbalch equation
  • Zero-order absorption model

Correct Answer: Michaelis–Menten equation: v = (Vmax · C)/(Km + C)

Q6. In PK/PD modeling, the Hill equation is used to describe:

  • Dose proportionality between drug mass and concentration
  • Sigmoidal concentration–effect relationships with slope (Hill) coefficient
  • First-pass metabolism in the liver
  • Partition coefficient of drug into membranes

Correct Answer: Sigmoidal concentration–effect relationships with slope (Hill) coefficient

Q7. Which metric helps compare predictive performance of QSAR models?

  • R², RMSE, and external validation statistics
  • Mixture boiling point
  • Visual inspection of structures only
  • pH of the medium

Correct Answer: R², RMSE, and external validation statistics

Q8. What is the principal aim of physiologically based pharmacokinetic (PBPK) models?

  • To model drug behavior using physiological compartments and organ-specific parameters
  • To predict chemical synthesis routes for APIs
  • To replace clinical trials entirely
  • To measure tablet hardness and friability

Correct Answer: To model drug behavior using physiological compartments and organ-specific parameters

Q9. Which method is commonly used for parameter estimation in nonlinear PK models?

  • Nonlinear least squares and maximum likelihood estimation
  • Simple arithmetic mean of observations
  • Qualitative expert opinion only
  • Fourier transform spectroscopy

Correct Answer: Nonlinear least squares and maximum likelihood estimation

Q10. What does clearance (Cl) represent pharmacokinetically?

  • Volume of plasma cleared of drug per unit time
  • Ratio of dose to bioavailability
  • Total volume of distribution at equilibrium
  • Absorption rate constant

Correct Answer: Volume of plasma cleared of drug per unit time

Q11. In population PK modeling, which term describes variability between individuals?

  • Residual unexplained variability
  • Interindividual variability (IIV)
  • Intragroup homogeneity
  • Analytical error only

Correct Answer: Interindividual variability (IIV)

Q12. Which criterion is used to compare non-nested models accounting for goodness-of-fit and complexity?

  • Akaike Information Criterion (AIC)
  • pH adjusted score
  • Partition coefficient (LogP)
  • Melting point

Correct Answer: Akaike Information Criterion (AIC)

Q13. What is the main purpose of sensitivity analysis in modeling?

  • To identify which parameters most influence model outputs
  • To determine tablet dissolution time experimentally
  • To calculate chemical yield in synthesis
  • To visualize molecular orbitals

Correct Answer: To identify which parameters most influence model outputs

Q14. Which technique is central to virtual screening and ligand–receptor interaction prediction?

  • Molecular docking and scoring
  • UV spectroscopy
  • Microbial culture tests
  • Tablet compression profiling

Correct Answer: Molecular docking and scoring

Q15. What does bioavailability (F) quantify?

  • Fraction of an administered dose reaching systemic circulation intact
  • Rate of renal elimination
  • Affinity of a ligand for a receptor
  • Solubility of the drug in water

Correct Answer: Fraction of an administered dose reaching systemic circulation intact

Q16. In two-compartment models, the distribution phase is primarily characterized by:

  • Rapid decline due to distribution between central and peripheral compartments
  • Steady-state concentration only
  • Zero-order elimination kinetics
  • Absorption from the GI tract

Correct Answer: Rapid decline due to distribution between central and peripheral compartments

Q17. Which descriptor is commonly used in QSAR to represent lipophilicity?

  • LogP (octanol–water partition coefficient)
  • Molecular weight only
  • Boiling point
  • pKa exclusively

Correct Answer: LogP (octanol–water partition coefficient)

Q18. What is model identifiability?

  • Ability to uniquely estimate model parameters from available data
  • Stability of a tablet formulation under stress
  • Number of compartments in a PBPK model
  • Strength of hydrogen bonding in a ligand

Correct Answer: Ability to uniquely estimate model parameters from available data

Q19. Monte Carlo simulation in drug design is used to:

  • Assess variability and uncertainty by random sampling of parameters
  • Measure melting point distributions experimentally
  • Determine chemical reaction pathways deterministically
  • Visualize protein secondary structure only

Correct Answer: Assess variability and uncertainty by random sampling of parameters

Q20. Which validation approach is best for assessing external predictive power of a QSAR model?

  • External validation with an independent test set
  • Inspecting training set R² only
  • Comparing scaffold images visually
  • Counting descriptor numbers

Correct Answer: External validation with an independent test set

Q21. What does steady state mean in repeated dosing?

  • Rate of drug administration equals rate of elimination, giving constant average concentration
  • Drug concentration reaches zero between doses
  • Maximum concentration is never achieved
  • Drug stops being absorbed after several doses

Correct Answer: Rate of drug administration equals rate of elimination, giving constant average concentration

Q22. Which parameter is directly proportional to half-life (t1/2) in a one-compartment model?

  • Clearance (inverse relationship)
  • Volume of distribution and ln2 divided by clearance (t1/2 = 0.693·Vd/Cl)
  • Absorption rate constant only
  • Bioavailability alone

Correct Answer: Volume of distribution and ln2 divided by clearance (t1/2 = 0.693·Vd/Cl)

Q23. Which is a common scoring metric for docking poses?

  • Estimated binding affinity (kcal/mol) from scoring functions
  • Tablet dissolution time
  • Protein expression level in cells
  • Melting point of ligand

Correct Answer: Estimated binding affinity (kcal/mol) from scoring functions

Q24. Allometric scaling is used to:

  • Predict pharmacokinetic parameters across species based on body size
  • Scale up tablet production batches only
  • Measure solubility changes with pH
  • Estimate receptor binding constants directly

Correct Answer: Predict pharmacokinetic parameters across species based on body size

Q25. What is the role of residual unexplained variability in PK models?

  • To capture measurement error and model misspecification
  • To represent the mean population parameter
  • To indicate perfect model fit
  • To determine partition coefficients

Correct Answer: To capture measurement error and model misspecification

Q26. In PK, bioavailability after oral dosing can be computed by comparing:

  • AUC oral divided by AUC IV, normalized for dose
  • Peak time (Tmax) only
  • Volume of distribution for oral vs IV
  • Elimination half-life only

Correct Answer: AUC oral divided by AUC IV, normalized for dose

Q27. Which method helps reduce overfitting in QSAR and machine learning models?

  • Cross-validation and regularization techniques
  • Using all available descriptors without selection
  • Maximizing descriptor count only
  • Ignoring external test performance

Correct Answer: Cross-validation and regularization techniques

Q28. Population pharmacokinetic models commonly use which software approach?

  • Nonlinear mixed-effects modeling (NLME)
  • Simple linear regression only
  • Graphical visualization without statistics
  • Manual curve fitting on paper

Correct Answer: Nonlinear mixed-effects modeling (NLME)

Q29. Which output indicates good predictive accuracy in regression-based QSAR?

  • High R² on training but low external R²
  • Low RMSE and high external validation R² (Q² ext)
  • Only high number of descriptors
  • High complexity irrespective of validation

Correct Answer: Low RMSE and high external validation R² (Q² ext)

Q30. What is a key advantage of integrating PK/PD modeling early in drug development?

  • Helps optimize dosing regimens and predict clinical outcomes, reducing late-stage failures
  • Eliminates the need for any experimental studies
  • Guarantees 100% success in clinical trials
  • Replaces chemistry in lead optimization entirely

Correct Answer: Helps optimize dosing regimens and predict clinical outcomes, reducing late-stage failures

Leave a Comment